Sunil Kumar Chawla – författare

The aim of this book is to provide insight into Data Science and Artificial Learning Techniques based on Industry 4.0, conveys how Machine Learning & Data Science are becoming an essential part of industrial and academic research. Varying from healthcare to social networking and everywhere hybrid models for Data Science, Al, and Machine Learning are being used. The book describes different theoretical and practical aspects and highlights how new systems are being developed.

Along with focusing on the research trends, challenges and future of AI in Data Science, the book explores the potential for integration of advanced AI algorithms, addresses the challenges of Data Science for Industry 4.0, covers different security issues, includes qualitative and quantitative research, and offers case studies with working models. This book also provides an overview of AI and Data Science algorithms for readers who do not have a strong mathematical background.

Undergraduates, postgraduates, academicians, researchers, and industry professionals will benefit from this book and use it as a guide.

The aim of this book is to provide insight into Data Science and Artificial Learning Techniques based on Industry 4.0, conveys how Machine Learning & Data Science are becoming an essential part of industrial and academic research. Varying from healthcare to social networking and everywhere hybrid models for Data Science, Al, and Machine Learning are being used. The book describes different theoretical and practical aspects and highlights how new systems are being developed.

Along with focusing on the research trends, challenges and future of AI in Data Science, the book explores the potential for integration of advanced AI algorithms, addresses the challenges of Data Science for Industry 4.0, covers different security issues, includes qualitative and quantitative research, and offers case studies with working models. This book also provides an overview of AI and Data Science algorithms for readers who do not have a strong mathematical background.

Undergraduates, postgraduates, academicians, researchers, and industry professionals will benefit from this book and use it as a guide.

Green engineering involves the designing, innovation, and commercialization of products and processes which promote sustainability without eliminating both efficiency and economic viability. This handbook focuses on sustainable development through green engineering and technology. It is intended to address the applications and issues involved in their practical implementation.

A new range of renewable-energy technologies, modified to provide green engineering, will be described in this handbook. It will explore all green technologies required to provide green engineering for the future.These include, but are not limited to, green smart buildings, fuel-efficient transportation, paperless offices, and many more energy-efficient measures.

Handbook of Sustainable Development through Green Engineering and Technology acts as a comprehensive reference book to use when identifying development for programs and sustainable initiatives within the current legislative framework. It aims to be of great interest to researchers, faculty members, and students across the globe.

Green engineering involves the designing, innovation, and commercialization of products and processes which promote sustainability without eliminating both efficiency and economic viability. This handbook focuses on sustainable development through green engineering and technology. It is intended to address the applications and issues involved in their practical implementation.

A new range of renewable-energy technologies, modified to provide green engineering, will be described in this handbook. It will explore all green technologies required to provide green engineering for the future.These include, but are not limited to, green smart buildings, fuel-efficient transportation, paperless offices, and many more energy-efficient measures.

Handbook of Sustainable Development through Green Engineering and Technology acts as a comprehensive reference book to use when identifying development for programs and sustainable initiatives within the current legislative framework. It aims to be of great interest to researchers, faculty members, and students across the globe.

The industrial landscape is changing rapidly, and so is global society. This change is driven by the growing adoption of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) technologies. IIoT and AI are transforming the way industrial engineering is done, enabling new levels of automation, productivity, and efficiency. However, as IIoT and AI become more pervasive in the industrial world, they also offer new security risks that must be addressed to ensure the reliability and safety of critical systems.

Industrial Internet of Things Security: Protecting AI-Enabled Engineering Systems in Cloud and Edge Environments provides a comprehensive guide to IIoT security, covering topics such as network architecture, risk management, data security, and compliance. It addresses the unique security challenges that the cloud and edge environments pose, providing practical guidance for securing IIoT networks in these contexts. It includes numerous real-world case studies and examples, providing readers with practical insights into how IIoT security and AI-enabled industrial engineering are being implemented in various industries. Best practices are emphasized for the readers to ensure the reliability, safety, and security of their systems while also learning the latest developments in IIoT security for AI-enabled industrial engineering systems in this rapidly evolving field.

By offering step-by-step guidance for the implantation process along with best practices, this book becomes a valuable resource for practitioners and engineers in the areas of industrial engineering, IT, computer engineering, and anyone looking to secure their IIoT network against cyber threats.